What SaaS metrics should a head of engineering track?
What SaaS metrics should a head of engineering track?
For an engineering leader at a startup, understanding and monitoring key SaaS metrics is crucial to drive growth, make informed decisions, and ensure the sustainable success of the product. There are, however, many SaaS related metrics, making it challenging to focus on the few that matter. Additionally, some metrics are only relevant to large and more mature SaaS companies as is the case with LTV - more on that in a bit.
In this post I offer the few that I track and why they matter. These metrics are categorized under growth, profitability and efficiency.
Growth metrics
All the growth metrics I look at are concerned with revenue, in one way or another. The three flavors of growth I look at are ARR, ACV and TCV.
ARR is a metric that represents the predictable and recurring revenue components of your subscription business on an annual basis. It excludes one-time payments and focuses solely on the revenue that is expected to recur every year. For example, if a customer subscribes to a service with a monthly fee of $100, the ARR from this customer would be $100 x 12 = $1,200.
ARR doesn’t take into account one time sources of revenue, like professional services or contracts that vary price or usage over time, which in turn vary revenue over time. The latter is very common with enterprise customers. To address the limitations of ARR, I also look at ACV and TVC.
ACV measures the average annualized revenue per customer contract, excluding any one-time fees (like setup fees). It's particularly useful for businesses with subscription models that have varying contract lengths or prices. ACV helps standardize the revenue expected per contract on an annual basis, making it easier to compare and forecast future revenues. For contracts that are not annual, the revenue is annualized. For instance, if a 2-year contract is worth $24,000, the ACV would be $24,000 / 2 = $12,000. Note, that even though ACV is $12,000, this doesn’t mean that ARR will be the same.
Finally, TCV represents the total revenue value of a contract, including all recurring revenue and one-time charges, over the entire contract period. TCV is useful for understanding the total expected revenue from a deal, especially for contracts that have varying lengths and may include a mix of one-time and recurring revenue components. For instance, if a customer signs a 3-year contract with an annual fee of $10,000 and an upfront services fee of $5,000, the TCV would be $10,000 x 3 + $5,000 = $35,000.
To recap, ARR provides a snapshot of the ongoing revenue base, ACV gives insight into the average annual value of contracts, and TCV offers a comprehensive look at the total value of contracts over their lifespan.
Profitability metrics
The main profitability metrics I look at are gross and operating margins. For latter stage companies, or ones with a positive operating income, I will also look at free cash flow (FCF). It’s extremely rate for a pre-IPO startup to have positive FCF, but it ultimately is the most crucial profitability measure.
I had previously written an article on cost of goods sold (COGS), margins and how engineering can impact those, especially gross margins for SaaS companies.
The structure of COGS will vary by industry. Most software companies, unless they build hardware, incur very low COGS relative to their revenues. For most software companies, especially SaaS, the two main cost items here are cloud/infrastructure costs and support
Efficiency metrics
The efficiency metrics are ones I look at over time. As a startup grows, so does it revenues and headcount, it should start exhibiting efficiency gains. These efficiency metrics help show that the startup is able to derive more revenue with fewer resources over time. The startup might not be profitable, as in +ve operating income or even better +ve FCF, but it is exhibiting signals of being able to become profitable via these metrics.
The first metric I look at is Cash Burn to Net New ARR (CB2NARR). This ratio compares the rate at which a company is spending (or "burning") its cash reserves to the rate at which it is adding new ARR, i.e. excluding revenue from existing customers (such as renewals or upgrades). Essentially, it provides insight into how effectively a company is using its cash to generate new sales and grow its recurring revenue base. A similar metric to use is to track Net New ARR per Head, which assumes that the majority of the cash burn is payroll and employee related.
A lower CB2NARR ratio indicates efficiency in using cash to drive new business, meaning the company generates a significant amount of new ARR for each dollar spent. This is often seen as a positive indicator of sustainable growth, especially if the company is effectively converting its investment into new revenue. Conversely, a higher ratio suggests that the company is spending a lot of cash relative to the new ARR it is generating. This could raise questions about the sustainability of the business model, especially if the high cash burn is not translating into significant new revenue growth.
In additional to this, I also look at spend per major organization as a function of sales. For example, I look at the operating expenses of R&D:Sales, S&M:Sales and so on to track spend relative to peers. You should also do that whilst also adjusting for company stage. A startup in the earliest stages will have a spend profile that is very different than one that has IPO-ed.
Fortunately there is a lot of data, at least for public companies, that track operating expense ratios across many SaaS companies. The table below, and more, is available from
’s most excellent Clouded Judgement substack. I had previously written on. this topic too and shared metrics for pre-IPO companies here
Leading up to the IPO, SaaS companies spent on median 24% of revenue on R&D. As you can see there is almost no deviation between the financials reported at IPO and 2 years prior (medians were 23% and 23% respectively) - Source: Blossom Street Ventures
These efficiency metrics are particularly relevant for evaluating how effectively a SaaS company is managing its growth strategy. Investors and executives use it to assess whether the company is on a path to profitability and how long it might take to reach that point based on the current rate of cash consumption and revenue growth.
What metrics do I not look at?
There’s one metric I tend to ignore and that is the customer life-time value (LTV) metric. This metric tries to measure the revenue, or even better profit, a company will derived from a customer throughput that customer’s lifetime with the company. It can be calculated. in two ways.
The first, illustrated below multiplies the average revenue per customer with the gross margins and average customer lifespan. It’s that last component of the LTV that I have concerns with. Should that be set to 3 years? 5 years? 10 years? For relatively young companies, there’s little to no track record or data to help find a good measure for this variable.
LTV = ARPU × Gross Margin × Average Customer Lifespan
The alternate way to calculate LTV is to model average customer lifespan as the inverse of churn rate. This one suffers from the same problem as its derivative one. It’s hard to find a stable churn rate for a startup, especially in earlier stages.
LTV = ARPU × Gross Margin × (1 / Churn Rate)
It’s not that I don’t care about LTV and its derivative metric - LTV/CAC - I just think they can be very difficult to get right in the early startup stages. And if they are modeled incorrectly can give a false sense of comfort.
I also tend to not focus early on on the Rule of 40, which I also think is more suited for mature SaaS companies.
So to recap, the list of metrics I track are below.
ARR/ACV/TCV
Gross and Operating Margins
Cash Burn : Net New ARR
Operating Expenses per major department : Sales
As is the case with metrics, they cannot be viewed or analyzed in isolation. A company with a very high cash burn to net new ARR might not necessarily be in trouble or poorly managed. It could be capitalizing on an opportunity to dramatically expand its customer base in the short-term and then drive profitability in the longer-run. It could also be increasing R&D investments to seize on market and product opportunity. Context and strategy matters when looking at metrics.